Human longevity is heritable, and statistically and biologically compelling genetic associations with longevity and age-related traits in humans have been identified. The translation of these genetic associations into insights that can lead to pharmacological interventions designed to promote healthy aging requires an approach and infrastructure that integrates many sources of information and scientific expertise. In fact, a previous inability to translate insights from genetic associations to longevity-promoting interventions is due, at least in part, to a lack of well-integrated and assembled research teams with expertise in all areas of relevance. We propose the creation of a resource and infrastructure that integrates genomic and related data sources that enable our diverse scientific team to develop strategies for identifying targets for pharmacological intervention that will impact longevity based on genetic associations. This infrastructure will include information from longitudinal cohort studies with genome-wide genotype and sequencing data, computational methods for annotating genetic variants, information from tissue-specific studies of expression quantitative trait loci (eQTL), and datasets of chemical properties of small molecule compounds linked to protein targets. Our scientific team includes experts in human and model organism aging, genetic epidemiology of aging, statistical genetics, chemical informatics, and pharmaceutical development. We will also assemble a research planning committee that will meet annually to evaluate the evidence from our statistical analyses and to develop plans for pilot projects to advance the translation of our findings into health-promoting therapeutics. A central theme in our proposal is to develop insights relating molecular and physiologic factors that can be manipulated pharmacologically to healthy aging based on hypothesis rooted in genetic associated studies involving longevity. We will identify candidate genetic variants for in-depth analysis by meta-analyzing results from published genome-wide association studies (GWAS) of longevity and age-related traits and by searching for evidence of genetic variants with pleiotropic effects on aging-related traits. Genes likely to be modulated by candidate genetic variants will be identified using genomic functional annotation resources such as tissue-specific genomic functional elements and eQTLs. For each identified gene, an allelic series of genetic variants associated with, e.g., the expression of that gene, will be identified from eQTL data sets, and a genetic risk score constructed from the allelic series will be tested for its association with longitudinal measures of aging, including incident disability, incident disease and chronic conditions, and change in physical and cognitive function, which can build the foundation for the search for small molecule compounds that might mimic the collective effect of selected genetic variants. By identifying small molecules based on therapeutic hypotheses relating genetic function to healthy aging, effective translational research strategies can be developed and disseminated to the research community.